A novel multi-objective co-evolutionary approach for supply chain gap analysis with consideration of uncertainties
A. Jafarian, M. Rabiee, M. Tavana, International Journal of Production Economics 228 (2020).
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Journal Article
| Published
| English
Author
Jafarian, Ahmad;
Rabiee, Meysam;
Tavana, MadjidLibreCat
Publishing Year
Journal Title
International Journal of Production Economics
Volume
228
Article Number
107852
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Jafarian A, Rabiee M, Tavana M. A novel multi-objective co-evolutionary approach for supply chain gap analysis with consideration of uncertainties. International Journal of Production Economics. 2020;228. doi:10.1016/j.ijpe.2020.107852
Jafarian, A., Rabiee, M., & Tavana, M. (2020). A novel multi-objective co-evolutionary approach for supply chain gap analysis with consideration of uncertainties. International Journal of Production Economics, 228, Article 107852. https://doi.org/10.1016/j.ijpe.2020.107852
@article{Jafarian_Rabiee_Tavana_2020, title={A novel multi-objective co-evolutionary approach for supply chain gap analysis with consideration of uncertainties}, volume={228}, DOI={10.1016/j.ijpe.2020.107852}, number={107852}, journal={International Journal of Production Economics}, publisher={Elsevier BV}, author={Jafarian, Ahmad and Rabiee, Meysam and Tavana, Madjid}, year={2020} }
Jafarian, Ahmad, Meysam Rabiee, and Madjid Tavana. “A Novel Multi-Objective Co-Evolutionary Approach for Supply Chain Gap Analysis with Consideration of Uncertainties.” International Journal of Production Economics 228 (2020). https://doi.org/10.1016/j.ijpe.2020.107852.
A. Jafarian, M. Rabiee, and M. Tavana, “A novel multi-objective co-evolutionary approach for supply chain gap analysis with consideration of uncertainties,” International Journal of Production Economics, vol. 228, Art. no. 107852, 2020, doi: 10.1016/j.ijpe.2020.107852.
Jafarian, Ahmad, et al. “A Novel Multi-Objective Co-Evolutionary Approach for Supply Chain Gap Analysis with Consideration of Uncertainties.” International Journal of Production Economics, vol. 228, 107852, Elsevier BV, 2020, doi:10.1016/j.ijpe.2020.107852.
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